Touch force estimation

ABSTRACT

A processing system for multiple input object force estimation includes sensor circuitry and processing circuitry. The sensor circuitry is configured to acquire measurements of a sensing region using sensor electrodes. The processing circuitry is connected to the sensor circuitry. The processing system is configured to obtain a delta image of the sensing region using the measurements, identify locations of the input objects in the sensing region using the delta image, and determine a force estimate for each input object using the delta image, a bending response model, and the plurality of locations. The processing system is further configured to perform an action based on the force estimate of each input object of the plurality of input objects.

FIELD

This invention generally relates to electronic devices.

BACKGROUND

Input devices, including proximity sensor devices (also commonly calledtouchpads or touch sensor devices), are widely used in a variety ofelectronic systems. A proximity sensor device typically includes asensing region, often demarked by a surface, in which the proximitysensor device determines the presence, location and/or motion of one ormore input objects. Proximity sensor devices may be used to provideinterfaces for the electronic system. For example, proximity sensordevices are often used as input devices for larger computing systems(such as opaque touchpads integrated in, or peripheral to, notebook ordesktop computers). Proximity sensor devices are also often used insmaller computing systems (such as touch screens integrated in cellularphones).

SUMMARY

In general, in one aspect, one or more embodiments relate to aprocessing system for multiple input object force estimation. Theprocessing system includes sensor circuitry and processing circuitry.The sensor circuitry is configured to acquire measurements of a sensingregion using sensor electrodes. The processing circuitry is connected tothe sensor circuitry. The processing system is configured to obtain adelta image of the sensing region using the measurements, identifylocations of the input objects in the sensing region using the deltaimage, and determine a force estimate for each input object using thedelta image, a bending response model, and the plurality of locations.The processing system is further configured to perform an action basedon the force estimate of each input object of the plurality of inputobjects.

In general, in one aspect, one or more embodiments relate to a methodfor multiple input object force estimation. The method includesobtaining a delta image of a sensing region using sensor electrodes,identifying locations of input objects in the sensing region using thedelta image, and determining a force estimate for each input objectusing the delta image, a bending response model, and the plurality oflocations. The method further includes performing an action based on theforce estimate of each input object of the plurality of input objects.

In general, in one aspect, one or more embodiments relate to an inputdevice for multiple input object force estimation. The input deviceincludes sensor circuitry configured acquire measurements of a sensingregion using sensor electrodes, and processing circuitry connected tothe sensor circuitry. The processing circuitry is configured to obtain adelta image of the sensing region using measurements, identify locationsof input objects in the sensing region using the delta image, anddetermine a force estimate for each input object using the delta image,a bending response model, and the locations. The processing circuitry isfurther configured to perform an action based on the force estimate ofeach input object.

Other aspects of the invention will be apparent from the followingdescription and the appended claims.

BRIEF DESCRIPTION OF DRAWINGS

The preferred exemplary embodiment of the present invention willhereinafter be described in conjunction with the appended drawings,where like designations denote like elements, and:

FIGS. 1 and 2 are a block diagram of an example system that includes aninput device in accordance with an embodiment of the invention;

FIGS. 3, 4.1, and 4.2 are example diagrams in accordance with one ormore embodiments of the invention;

FIGS. 5, 6, and 7 are example flowcharts in accordance with one or moreembodiments of the invention; and

FIGS. 8 and 9 are example graphs in accordance with one or moreembodiments of the invention.

DETAILED DESCRIPTION

The following detailed description is merely exemplary in nature, and isnot intended to limit the invention or the application and uses of theinvention. Furthermore, there is no intention to be bound by anyexpressed or implied theory presented in the preceding technical field,background, brief summary or the following detailed description.

In the following detailed description of embodiments of the invention,numerous specific details are set forth in order to provide a morethorough understanding of the invention. However, it will be apparent toone of ordinary skill in the art that the invention may be practicedwithout these specific details. In other instances, well-known featureshave not been described in detail to avoid unnecessarily complicatingthe description.

Throughout the application, ordinal numbers (e.g., first, second, third,etc.) may be used as an adjective for an element (i.e., any noun in theapplication). The use of ordinal numbers is not to imply or create anyparticular ordering of the elements nor to limit any element to beingonly a single element unless expressly disclosed, such as by the use ofthe terms “before”, “after”, “single”, and other such terminology.Rather, the use of ordinal numbers is to distinguish between theelements. By way of an example, a first element is distinct from asecond element, and the first element may encompass more than oneelement and succeed (or precede) the second element in an ordering ofelements.

Various embodiments of the present invention provide input devices andmethods that facilitate improved usability.

Turning now to the figures, FIG. 1 is a block diagram of an exemplaryinput device (100), in accordance with embodiments of the invention. Theinput device (100) may be configured to provide input to an electronicsystem (not shown). As used in this document, the term “electronicsystem” (or “electronic device”) broadly refers to any system capable ofelectronically processing information. Some non-limiting examples ofelectronic systems include personal computers of all sizes and shapes,such as desktop computers, laptop computers, netbook computers, tablets,web browsers, e-book readers, and personal digital assistants (PDAs).Additional example electronic systems include composite input devices,such as physical keyboards that include an input device and separatejoysticks or key switches. Further example electronic systems includeperipherals, such as data input devices (including remote controls andmice), and data output devices (including display screens and printers).Other examples include remote terminals, kiosks, and video game machines(e.g., video game consoles, portable gaming devices, and the like).Other examples include communication devices (including cellular phones,such as smart phones) and media devices (including recorders, editors,and players such as televisions, set-top boxes, music players, digitalphoto frames, and digital cameras). Additionally, the electronic systemcould be a host or a slave to the input device.

The input device (100) may be implemented as a physical part of theelectronic system or may be physically separate from the electronicsystem. Further, portions of the input device (100) may be part of theelectronic system. For example, all or part of the determination modulemay be implemented in the device driver of the electronic system. Asappropriate, the input device (100) may communicate with parts of theelectronic system using any one or more of the following: buses,networks, and other wired or wireless interconnections. Examples includeI2C, SPI, PS/2, Universal Serial Bus (USB), Bluetooth, RF, and IRDA.

In FIG. 1, the input device (100) is shown as a proximity sensor device(also often referred to as a “touchpad” or a “touch sensor device”)configured to sense input provided by one or more input objects (140) ina sensing region (120). Example input objects include fingers and styli,as shown in FIG. 1. Throughout the specification, the singular form ofinput object is used. Although the singular form is used, multiple inputobjects may exist in the sensing region (120). Further, which particularinput objects are in the sensing region may change over the course ofone or more gestures. To avoid unnecessarily complicating thedescription, the singular form of input object is used and refers to allof the above variations.

The sensing region (120) encompasses any space above, around, in and/ornear the input device (100) in which the input device (100) is able todetect user input (e.g., user input provided by one or more inputobjects (140)). The sizes, shapes, and locations of particular sensingregions may vary widely from embodiment to embodiment.

In some embodiments, the sensing region (120) extends from a surface ofthe input device (100) in one or more directions into space untilsignal-to-noise ratios prevent sufficiently accurate object detection.The extension above the surface of the input device may be referred toas the above surface sensing region. The distance to which this sensingregion (120) extends in a particular direction, in various embodiments,may be on the order of less than a millimeter, millimeters, centimeters,or more, and may vary significantly with the type of sensing technologyused and the accuracy desired. Thus, some embodiments sense input thatcomprises no contact with any surfaces of the input device (100),contact with an input surface (e.g. a touch surface) of the input device(100), contact with an input surface of the input device (100) coupledwith some amount of applied force or pressure, and/or a combinationthereof. In various embodiments, input surfaces may be provided bysurfaces of casings within which the sensor electrodes reside, by facesheets applied over the sensor electrodes or any casings, etc. In someembodiments, the sensing region (120) has a rectangular shape whenprojected onto an input surface of the input device (100).

The input device (100) may utilize any combination of sensor componentsand sensing technologies to detect user input in the sensing region(120). The input device (100) includes one or more sensing elements fordetecting user input. As several non-limiting examples, the input device(100) may use capacitive, elastive, resistive, inductive, magnetic,acoustic, ultrasonic, and/or optical techniques.

Some implementations are configured to provide images that span one,two, three, or higher-dimensional spaces. Some implementations areconfigured to provide projections of input along particular axes orplanes. Further, some implementations may be configured to provide acombination of one or more images and one or more projections.

In some resistive implementations of the input device (100), a flexibleand conductive first layer is separated by one or more spacer elementsfrom a conductive second layer. During operation, one or more voltagegradients are created across the layers. Pressing the flexible firstlayer may deflect it sufficiently to create electrical contact betweenthe layers, resulting in voltage outputs reflective of the point(s) ofcontact between the layers. These voltage outputs may be used todetermine positional information.

In some inductive implementations of the input device (100), one or moresensing elements pick up loop currents induced by a resonating coil orpair of coils. Some combination of the magnitude, phase, and frequencyof the currents may then be used to determine positional information.

In some capacitive implementations of the input device (100), voltage orcurrent is applied to create an electric field. Nearby input objectscause changes in the electric field and produce detectable changes incapacitive coupling that may be detected as changes in voltage, current,or the like.

Some capacitive implementations utilize arrays or other regular orirregular patterns of capacitive sensing elements to create electricfields. In some capacitive implementations, separate sensing elementsmay be ohmically shorted together to form larger sensor electrodes. Somecapacitive implementations utilize resistive sheets, which may beuniformly resistive.

Some capacitive implementations utilize “self capacitance” (or “absolutecapacitance”) sensing methods based on changes in the capacitivecoupling between sensor electrodes and an input object. In variousembodiments, an input object near the sensor electrodes alters theelectric field near the sensor electrodes, thus changing the measuredcapacitive coupling. In one implementation, an absolute capacitancesensing method operates by modulating sensor electrodes with respect toa reference voltage (e.g., system ground) and by detecting thecapacitive coupling between the sensor electrodes and input objects. Thereference voltage may be a substantially constant voltage or a varyingvoltage and in various embodiments; the reference voltage may be systemground. Measurements acquired using absolute capacitance sensing methodsmay be referred to as absolute capacitive measurements.

Some capacitive implementations utilize “mutual capacitance” (or “transcapacitance”) sensing methods based on changes in the capacitivecoupling between sensor electrodes. In various embodiments, an inputobject near the sensor electrodes alters the electric field between thesensor electrodes, thus changing the measured capacitive coupling. Inone implementation, a mutual capacitance sensing method operates bydetecting the capacitive coupling between one or more transmitter sensorelectrodes (also “transmitter electrodes” or “transmitter”) and one ormore receiver sensor electrodes (also “receiver electrodes” or“receiver”). Transmitter sensor electrodes may be modulated relative toa reference voltage (e.g., system ground) to transmit transmittersignals. Receiver sensor electrodes may be held substantially constantrelative to the reference voltage to facilitate receipt of resultingsignals. The reference voltage may be a substantially constant voltageand, in various embodiments, the reference voltage may be system ground.In some embodiments, transmitter sensor electrodes may both bemodulated. The transmitter electrodes are modulated relative to thereceiver electrodes to transmit transmitter signals and to facilitatereceipt of resulting signals. A resulting signal may include effect(s)corresponding to one or more transmitter signals and/or to one or moresources of environmental interference (e.g., other electromagneticsignals). The effect(s) may be the transmitter signal, a change in thetransmitter signal caused by one or more input objects and/orenvironmental interference, or other such effects. Sensor electrodes maybe dedicated transmitters or receivers, or may be configured to bothtransmit and receive. Measurements acquired using mutual capacitancesensing methods may be referred to as mutual capacitance measurements.

Further, the sensor electrodes may be of varying shapes and/or sizes.The same shapes and/or sizes of sensor electrodes may or may not be inthe same groups. For example, in some embodiments, receiver electrodesmay be of the same shapes and/or sizes while, in other embodiments,receiver electrodes may be varying shapes and/or sizes.

In FIG. 1, a processing system (110) is shown as part of the inputdevice (100). The processing system (110) is configured to operate thehardware of the input device (100) to detect input in the sensing region(120). The processing system (110) includes parts of, or all of, one ormore integrated circuits (ICs) and/or other circuitry components. Forexample, a processing system for a mutual capacitance sensor device mayinclude transmitter circuitry configured to transmit signals withtransmitter sensor electrodes and/or receiver circuitry configured toreceive signals with receiver sensor electrodes. Further, a processingsystem for an absolute capacitance sensor device may include drivercircuitry configured to drive absolute capacitance signals onto sensorelectrodes and/or receiver circuitry configured to receive signals withthose sensor electrodes. In one or more embodiments, a processing systemfor a combined mutual and absolute capacitance sensor device may includeany combination of the above described mutual and absolute capacitancecircuitry. In some embodiments, the processing system (110) alsoincludes electronically-readable instructions, such as firmware code,software code, and/or the like. In some embodiments, componentscomposing the processing system (110) are located together, such as nearsensing element(s) of the input device (100). In other embodiments,components of processing system (110) are physically separate with oneor more components being close to the sensing element(s) of the inputdevice (100) and one or more components being elsewhere. For example,the input device (100) may be a peripheral coupled to a computingdevice, and the processing system (110) may include software configuredto run on a central processing unit of the computing device and on oneor more ICs (perhaps with associated firmware) separate from the centralprocessing unit. As another example, the input device (100) may bephysically integrated in a mobile device, and the processing system(110) may include circuits and firmware that are part of a mainprocessor of the mobile device. In some embodiments, the processingsystem (110) is dedicated to implementing the input device (100). Inother embodiments, the processing system (110) also performs otherfunctions, such as operating display screens, driving haptic actuators,etc.

The processing system (110) may be implemented as a set of modules thathandle different functions of the processing system (110). Each modulemay include circuitry that is a part of the processing system (110),firmware, software, or a combination thereof. In various embodiments,different combinations of modules may be used. For example, as shown inFIG. 1, the processing system (110) may include a determination module(150) and a sensor module (160). The determination module (150) mayinclude functionality to determine when at least one input object is ina sensing region, determine signal to noise ratio, determine positionalinformation of an input object, identify a gesture, determine an actionto perform based on the gesture, a combination of gestures or otherinformation, and/or perform other operations.

The sensor module (160) may include functionality to drive the sensingelements to transmit transmitter signals and receive the resultingsignals. For example, the sensor module (160) may include sensorycircuitry that is coupled to the sensing elements. The sensor module(160) may include, for example, a transmitter module and a receivermodule. The transmitter module may include transmitter circuitry that iscoupled to a transmitting portion of the sensing elements. The receivermodule may include receiver circuitry coupled to a receiving portion ofthe sensing elements and may include functionality to receive theresulting signals.

Although FIG. 1 shows only a determination module (150) and a sensormodule (160), alternative or additional modules may exist in accordancewith one or more embodiments of the invention. Such alternative oradditional modules may correspond to distinct modules or sub-modulesthan one or more of the modules discussed above. Example alternative oradditional modules include hardware operation modules for operatinghardware such as sensor electrodes and display screens, data processingmodules for processing data such as sensor signals and positionalinformation, reporting modules for reporting information, identificationmodules configured to identify gestures, such as mode changing gestures,and mode changing modules for changing operation modes. Further, thevarious modules may be combined in separate integrated circuits. Forexample, a first module may be comprised at least partially within afirst integrated circuit and a separate module may be comprised at leastpartially within a second integrated circuit. Further, portions of asingle module may span multiple integrated circuits. In someembodiments, the processing system as a whole may perform the operationsof the various modules.

In some embodiments, the processing system (110) responds to user input(or lack of user input) in the sensing region (120) directly by causingone or more actions. Example actions include changing operation modes,as well as graphical user interface (GUI) actions such as cursormovement, selection, menu navigation, and other functions. In someembodiments, the processing system (110) provides information about theinput (or lack of input) to some part of the electronic system (e.g. toa central processing system of the electronic system that is separatefrom the processing system (110), if such a separate central processingsystem exists). In some embodiments, some part of the electronic systemprocesses information received from the processing system (110) to acton user input, such as to facilitate a full range of actions, includingmode changing actions and GUI actions.

For example, in some embodiments, the processing system (110) operatesthe sensing element(s) of the input device (100) to produce electricalsignals indicative of input (or lack of input) in the sensing region(120). The processing system (110) may perform any appropriate amount ofprocessing on the electrical signals in producing the informationprovided to the electronic system. For example, the processing system(110) may digitize analog electrical signals obtained from the sensorelectrodes. As another example, the processing system (110) may performfiltering or other signal conditioning. As yet another example, theprocessing system (110) may subtract or otherwise account for abaseline, such that the information reflects a difference between theelectrical signals and the baseline. As yet further examples, theprocessing system (110) may determine positional information, recognizeinputs as commands, recognize handwriting, and the like.

“Positional information” as used herein broadly encompasses absoluteposition, relative position, velocity, acceleration, and other types ofspatial information. Exemplary “zero-dimensional” positional informationincludes near/far or contact/no contact information. Exemplary“one-dimensional” positional information includes positions along anaxis. Exemplary “two-dimensional” positional information includesmotions in a plane. Exemplary “three-dimensional” positional informationincludes instantaneous or average velocities in space. Further examplesinclude other representations of spatial information. Historical dataregarding one or more types of positional information may also bedetermined and/or stored, including, for example, historical data thattracks position, motion, or instantaneous velocity over time.

In some embodiments, the input device (100) is implemented withadditional input components that are operated by the processing system(110) or by some other processing system. These additional inputcomponents may provide redundant functionality for input in the sensingregion (120) or some other functionality. FIG. 1 shows buttons (130)near the sensing region (120) that may be used to facilitate selectionof items using the input device (100). Other types of additional inputcomponents include sliders, balls, wheels, switches, and the like.Conversely, in some embodiments, the input device (100) may beimplemented with no other input components.

In some embodiments, the input device (100) includes a touch screeninterface, and the sensing region (120) overlaps at least part of anactive area of a display screen. For example, the input device (100) mayinclude substantially transparent sensor electrodes overlaying thedisplay screen and provide a touch screen interface for the associatedelectronic system. The display screen may be any type of dynamic displaycapable of displaying a visual interface to a user and may include anytype of light emitting diode (LED), organic LED (OLED), cathode ray tube(CRT), liquid crystal display (LCD), plasma, electroluminescence (EL),or other display technology. The input device (100) and the displayscreen may share physical elements. For example, some embodiments mayutilize some of the same electrical components for displaying andsensing. In various embodiments, one or more display electrodes of adisplay device may be configured for both display updating and inputsensing. As another example, the display screen may be operated in partor in total by the processing system (110).

It should be understood that while many embodiments of the invention aredescribed in the context of a fully-functioning apparatus, themechanisms of the present invention are capable of being distributed asa program product (e.g., software) in a variety of forms. For example,the mechanisms of the present invention may be implemented anddistributed as a software program on information-bearing media that arereadable by electronic processors (e.g., non-transitorycomputer-readable and/or recordable/writable information bearing mediathat is readable by the processing system (110)). Additionally, theembodiments of the present invention apply equally regardless of theparticular type of medium used to carry out the distribution. Forexample, software instructions in the form of computer readable programcode to perform embodiments of the invention may be stored, in whole orin part, temporarily or permanently, on a non-transitorycomputer-readable storage medium. Examples of non-transitory,electronically-readable media include various discs, physical memory,memory, memory sticks, memory cards, memory modules, and or any othercomputer readable storage medium. Electronically-readable media may bebased on flash, optical, magnetic, holographic, or any other storagetechnology.

Although not shown in FIG. 1, the processing system, the input device,and/or the host system may include one or more computer processors,associated memory (e.g., random access memory (RAM), cache memory, flashmemory, etc.), one or more storage device(s) (e.g., a hard disk, anoptical drive such as a compact disk (CD) drive or digital versatiledisk (DVD) drive, a flash memory stick, etc.), and numerous otherelements and functionalities. The computer processor(s) may be anintegrated circuit for processing instructions. For example, thecomputer processor(s) may be one or more cores or micro-cores of aprocessor. Further, one or more elements of one or more embodiments maybe located at a remote location and connected to the other elements overa network. Further, embodiments of the invention may be implemented on adistributed system having several nodes, where each portion of theinvention may be located on a different node within the distributedsystem. In one embodiment of the invention, the node corresponds to adistinct computing device. Alternatively, the node may correspond to acomputer processor with associated physical memory. The node mayalternatively correspond to a computer processor or micro-core of acomputer processor with shared memory and/or resources.

FIG. 2 shows a block diagram of an example system in accordance with oneor more embodiments of the invention. In particular, FIG. 2 shows across section view of an electronic system (200) having an input devicein accordance with one or more embodiments of the invention. Theelectronic system may be a smart phone, a tablet computing device, atouchscreen, a computing device with a touchpad, or other device. Asshown in FIG. 2, the electronic system (200) includes at least a housing(202) and an input device. The electronic system (200) may includeadditional components, such as a central processing unit, memory,controllers, and other components that are not shown.

The housing (202) may be metal, plastic, other material, or acombination of materials. The housing (202) may be referred to as theframe of the electronic system (200) and may hold the input device.

The input device includes an input surface (204), a display (206), and acompressible layer (208). The input surface (204) is the surface of theinput device that may be touched by an input object. For example, theinput surface (204) may be glass or other material. The display (206) isa physical device that is configured to present visual information to auser. The input surface (204) and display (206) have bending propertiesthat define the amount of bending by the input surface (204) and display(206) in response to force at various locations along the input surface.In other words, the bending properties of the input surface (204) anddisplay (206) refer to the amount of bend of the input surface (204) anddisplay (206) when subjected to an external force onto the input surface(204) and display (206). The input surface (204) and display (206) maybe treated as having single bending properties or individual bendingproperties. Although FIG. 2 shows a distinct input surface (204) anddisplay (206), the input surface may be an uppermost part of thedisplay.

One or more fasteners (e.g., fastener X (210), fastener Y (212)) mayconnect the input surface (204) and the display (206) to the housing(202) at attachment points (e.g., attachment point X (214), attachmentpoint Y (216)). For example, the fastener may be an adhesive (e.g.,weld, solder, cement, glue), crimping, a mounting bracket or otherhardware connector, or other type of fastener. The attachment points(e.g., attachment point X (214), attachment point Y (216)) are thepoints at which the fastener connects the input surface (204) anddisplay (206) to the housing (202). For example, the attachment pointsmay be around the edges of the input surface and/or the display. Otherattachment points may exist without departing from the scope of theinvention. The fastener may affect the bending properties of the of theinput surface (204) and display (206). In other words, the amount ofbend may change depending on the type of fastener used and the locationof the attachment points. The bending properties are discussed inadditional detail with reference to FIG. 3.

Continuing with FIG. 2, the compressible layer (208) is a layer of theinput device that is configured to compress at least vertically inresponse to force applied to the input surface (204). In particular, thecompressible layer may include one or more compressible materials. Forexample, the compressible layer (208) may include foam, air gap, rubber,or other compressible material.

Continuing with FIG. 2, the input device may further include sensorelectrodes (not shown). The sensor electrodes may include one or moretouch electrodes and one or more force electrodes. The touch electrodesare configured to detect the presence of input object on or above theinput surface. In other words, if the sensor electrodes are capacitiveelectrodes, the capacitance measured using the touch electrodes isaffected by the presence of at least one input object. The forceelectrodes are electrodes that are configured to sense the amount offorce applied by at least one input object. For example, the capacitancemeasured by the force electrode is affected by the amount of forceapplied by an input object on the input surface. The force electrodesmay be the same electrodes as the touch electrodes. Further, the forceand/or touch electrodes may be the same electrodes used for the displayupdating.

In one or more embodiments of the invention, the capacitance measured bythe force electrode(s) is affected by the amount of vertical compressionof the compressible layer. In other words, a force electrode measuresthe amount of compression response of the compressible layer. Thecompression response may also be referred to as the conductive response,which is provided by the compression of the compressible layer. Variousforce sensing technologies having various configurations of forceelectrodes may be used. For example, the force sensing may be based onmutual capacitance or absolute capacitance sensing. The force electrodesmay be above, below, and/or in the middle of the compressible layer inaccordance with one or more embodiments of the invention. The followingare some examples of configurations of force electrodes.

By way of a first example, a force electrode may be above or within atop section of the compressible layer, and at least the section of thehousing below the compressible layer may include conductive material. Inthe example, when the compressible layer is compressed and the forceelectrode is driven with a sensing signal, the resulting signal includesthe effects of the decreased distance to the housing. A similar effectmay be achieved by putting the one or more force electrodes within alower section or underneath the compressible layer and having aconductive material above the compressible layer. By way of anotherexample, a force electrode may be above the compressible layer and aforce electrode may be below the compressible layer. In the example,mutual capacitive measurements acquired between the two electrodesidentifies the distance between the two electrodes and thus the amountof compression of the compressible layer. Based on the amount ofcompression, a determination may be made as to the amount of forceapplied to the input surface. In general, almost any force sensingtechnology may be used in one or more embodiments of the invention.

Turning to FIG. 3, FIG. 3 shows an example diagram in accordance withone or more embodiments of the invention. In particular, FIG. 3 shows atop down view of an example input surface (300) and corresponding pixeldiagram (302). In the example, consider a scenario in which a userapplies a first force to touch position X (304) and concurrently appliesa second force to touch position Y (306). The first force and the secondforce may be the same magnitude or different magnitudes. The applicationof the force results in a bending of the input surface and display.

Because of the attachment of the input surface and the display to thehousing, the amount of bending of the display at a location on the inputsurface is related to the distance from the attachment points to thelocation. For example, if the attachment points are around the edges ofthe input surface, then the input surface (300) may deflect less aroundthe edges of the input surface (300) and deflect more towards the centerof the input surface. In other words, the bending properties may radiateinward toward the middle, whereby less bending is around the edges andmore bending occurs toward middle when an equal amount of force isapplied. In some instances, where additional or different attachmentpoint(s) exists or other effects exist, the bending properties areirregular. For example, the bending properties that are accounted for bya compressible layer may include the effects of apertures in thecompressible layer to account for electrical and other connectorsthrough the compressible layer that support the sensors and display.

The bending may cause sensor electrodes to move closer to each other inthe case of mutual capacitive force sensing and/or cause sensorelectrodes to move closer to conductive surfaces in the case of absolutecapacitive sensing. Thus, a change in the measured capacitance isreceived. The sensor electrodes that measure force may be related topixels. In other words, each pixel may have a corresponding rawmeasurement value for the pixel that is obtained using one or moresensor electrodes. In the example diagram of FIG. 3, a pixel is a squarein the grid. However, a pixel may be triangular, or a different shape ormay be non-uniform shapes without departing from the scope of theinvention. Further, although FIG. 3 shows the input surface as having180 pixels, more or fewer pixels may exist without departing from thescope of the invention. For example, in some implementations, only ninepixels may exist.

As shown in the example pixel diagram (302), when force is applied attouch position X (304) and touch position Y (306), measurements areacquired for each pixel of the sensing region. In particular, eachlocation of the sensing region may have a corresponding bending responseto the force at the touch positions. For example, in response to theforce at touch position X (304) and touch position Y (306), a bendingresponse is exhibited at example pixel (308). The variation in bendingresponse based on the configuration of the electronic system may resultin the example pixel (308) having a greater bending response than thetouch positions. In other words, the delta image, or sensing imagegenerated by scanning the sensing region and having the baselineremoved, may have a greater value in some force configurations atexample pixel (308) than the pixels under the touch position. Further,even if a greater amount of force is applied to touch position Y (306)than touch position X (304), touch position Y (306) may have a lowerbending response than touch position X (304) resulting in a lower valuein the delta image.

One or more embodiments are directed to generating an estimation offorce separately for each input object using the delta image andcalibration data gathered for pixels of the sensing region. In otherwords, one or more embodiments generate an individual estimation of theforce applied by each input object of multiple input objects that areconcurrently on the sensing region. In the example of FIG. 3, one ormore embodiments generate a force value for touch position X (304) thatis an estimate of the force applied to touch position X (304) and aseparate force value for touch position Y (306) that is an estimate ofthe force applied to touch position Y (306). To generate the estimate,one or more embodiments use calibration data generated by a single inputobject being in the sensing region when the calibration data isobtained.

FIGS. 4.1 and 4.2 shows example diagrams for obtaining calibration datain accordance with one or more embodiments of the invention. In FIG.4.1, a test object (400) is placed on the sensing region (402) with aforce applied. The test object is an input object used for calibration.For example, the test object may be a slug. The amount of force ispre-defined in one or more embodiments. In one or more embodiments, thetest object is approximately the same size as an average finger. Forexample, the finger size may be an average adult finger within a definedconfidence interval. By way of a more specific example, the test objectmay be around 1.6 to 2 centimeters, with a degree of variabilityapplied.

For calibration, the test object (400) is placed at a position on thesensing region (402), and a model force image (not shown) of the sensingregion is acquired. The test object is moved to a new position, and anew model force image is acquired. Thus, for calibration, multiple modelforce images are acquired for each of the multiple positions. The shadedpixels in FIG. 4.1 correspond to positions in which the test object isplaced and a model force image obtained. In the embodiment shown, thetest object is placed at each position of the sensing region and a modelforce image is acquired for each position. Further, in the embodimentshown, the positions are overlapping. In some embodiments, the positionsare non-overlapping during calibration. In some embodiments, thepositions in which the test objects are placed and the model force imageacquired are separated by a certain distance. By way of an example, thetest object may be placed in six positions of the sensing region shownin FIG. 4.1 rather than all of the positions of the sensing region.Thus, at least some of the positions may not have a test object placedon the position. In such a scenario, linear interpolation may be used tointerpolate the model force image during runtime when a test object isplaced in a position in which the model force image does not exist.

The model force image is an image of the sensing region that has a valuefor each pixel of the sensing region. In one or more embodiments, themodel force image is a delta image. Additionally, or alternatively, themodel force image may be normalized based on the amount of force appliedwith the test object.

The combination of model force images form a bending response model(404). In other words, the bending response model (404) includes modelforce images for different positions of the sensing region in which atest object (400) is placed, whereby each model force image includes avalue for each pixel of the sensing region.

Turning to FIG. 4.2, rather than a finger size test object, the testobject (450) is one cell size. A cell (e.g., example cell (452)) is apartition of the sensing region. In other words, the surface sensingregion (402) is partitioned into a defined number of cells. In theexample shown in FIG. 4.2, the cell is a pixel size, whereby each pixelis smaller than the size of a finger. In some embodiments, the number ofcells is greater than the number of pixels. For example, the number offorce pixels may be nine and the number of cells may be forty-five. Insome embodiments, the number of cells is greater than the number ofpixels. In other words, the size of the electrodes and cells may beindependent of the cells. Using the cell-sized test object (450), asimilar calibration as described above with reference to FIG. 4.1 may beperformed.

While FIGS. 1, 2, 3, 4.1 and 4.2 show a configuration of components,other configurations may be used without departing from the scope of theinvention. For example, various components may be combined to create asingle component. As another example, the functionality performed by asingle component may be performed by two or more components. Further,the various configurations disclosed herein may be combined in virtuallyany contemplated manner.

FIGS. 5, 6, and 7 show flowcharts in accordance with one or moreembodiments of the invention. While the various steps in theseflowcharts are presented and described sequentially, one of ordinaryskill will appreciate that some or all of the steps may be executed indifferent orders, may be combined or omitted, and some or all of thesteps may be executed in parallel. Furthermore, the steps may beperformed actively or passively. For example, some steps may beperformed using polling or be interrupt driven in accordance with one ormore embodiments of the invention. By way of an example, determinationsteps may not require a processor to process an instruction unless aninterrupt is received to signify that condition exists in accordancewith one or more embodiments of the invention. As another example,determination steps may be performed by performing a test, such aschecking a data value to test whether the value is consistent with thetested condition in accordance with one or more embodiments of theinvention.

In Step 501, a test object is placed on a location of the sensing regionwith a defined force in accordance with one or more embodiments of theinvention. In other words, the test object is applied to the sensingregion with a defined amount force exerted in a defined direction on thesensing region. In one or more embodiments, the direction of the forceis perpendicular to the plane of the sensing region. The amount of forceis defined in that the amount of force is a fixed value. For example, arobot may exert a slug on the sensing region with a defined amount offorce. By way of another example, the test object having a known weightmay be placed on the sensing region, such that the force is caused bygravity of the test object. Other mechanisms may be used withoutdeparting from the scope of the invention.

In Step 503, a raw image of the sensing region is obtained while thetest object is on the location in accordance with one or moreembodiments of the invention. In one or more embodiments, the raw imageis from absolute and/or mutual capacitive measurements of the sensingregion. Absolute capacitance or self capacitance is determined bydetermining the amount of electric charge is added to a sensor electrodeto increase the electric potential of the sensor electrode by one unit.In one or more embodiments of the invention, the amount of electricpotential is affected by the distance to the housing and, subsequently,the compression of the compressible layer as affected by force. Todetermine the absolute capacitance, the sensor electrodes are drivenwith a modulated sensing signal to determine the amount of electriccharge. Measurements at each sensor electrode are obtained. For example,the measurements may be obtained at once or at different times. Mutualcapacitance measurements may be obtained by transmitting with atransmitter electrode (e.g., a sensor electrode) a transmitter signal.Resulting signals are received using another sensor electrode, which isthe receiver electrode. In one or more embodiments of the invention, theresulting signals are affected by the distance between the transmitterelectrode and receiver electrode and, subsequently, the compression ofthe compressible layer as affected by force. Regardless of whethermutual capacitive measurements or absolute capacitive measurements areused, the measurements may be combined into a raw image.

In Step 505, a delta image is determined from the raw image to obtain aforce image in accordance with one or more embodiments of the invention.The delta image is the measurements of the raw image that accounts forthe baseline. In other words, the delta image is the raw image with thebackground capacitance and the noise removed. Determining the deltaimage may be performed, for example, by subtracting values in thebaseline from corresponding values in the raw image. If the delta imageincludes touch as well as force information, additional steps may beperformed to obtain a force image from the delta image. For example, thesteps of FIG. 7 may be performed to perform the conversion. In someembodiments, the test object is a non-conductive material, such as wood.Thus, even though the sensor electrodes may be arranged to obtain bothtouch and force information in a single image, the delta image acquiredmay be a force image because the mere touch of the non-conductivematerial is not reflected in the image.

In Step 507, the force image is converted to a displacement image inaccordance with one or more embodiments of the invention. For example,the delta values in the delta image may be converted to displacementvalues using a parallel plate capacitance formula and some assumptionsabout the sensor stack-up of the sensor electrodes and compressiblelayer in the electronic system. The conversion may be based on the areaof the electrode, the dielectric constants of the layers under thedisplay, the thickness of the display, the thickness of the compressiblelayer, and the partial force at the location at which the conversion isbeing performed. Other techniques for performing the conversion may beused without departing from the scope of the invention.

Further, in some embodiments, no conversion is performed. For example,calibration and runtime may use the force image directly withoutconverting to a displacement image. In such a scenario, the discussionbelow with respect to displacement image may be performed using theforce image or delta image.

In Step 509, the displacement image is normalized based on the definedforce in accordance with one or more embodiments of the invention. Inone or more embodiments normalizing the displacement image includesdividing the displacement image by the defined force value. In one ormore embodiments, the normalizing the image is performed by dividingeach value in the image by the square root of the sum of the squares ofthe pixel values in the image. In such embodiments, the norm of theimage is one.

In Step 511, a determination is made whether another location exists toplace the test object. In particular, a determination is made whether tomove the test input object to a new location and get additionalcalibration data. In one or more embodiments, the number of positions isdependent on the amount of acceptable error as well as the amount ofstorage for data. In particular, each position results in storage ofcalibration data as well as a reduction in error for determining force.The positions and number of positions may be predefined as aconfiguration parameters based on the storage and error requirements. Ifa determination is made to use another location, the process repeatsstarting with Step 501.

Continuing with FIG. 5, in Step 513, dot products are precomputed inaccordance with one or more embodiments of the invention. In someembodiments, dot products between each pair of delta images areprecomputed and the precomputed dot products are stored. By way of anexample, consider the following, vector a_(i) is the flattened imagewhen the test object is at position i, and vector a_(j) is the flattenedimage when the test object is at position j. A flattened image is a twodimensional image that is converted into a one dimensional vector,without loss of information. For example, each row may be successivelystored in a one dimensional vector (e.g., p_(0,0), . . . , p_(0,n),p_(1,0) . . . , p_(1,n), p_(2,0), . . . , p_(2,n), . . . , p_(m,0), . .. p_(m,n)), where p_(i,j) is the value of the pixel at position row i,column j. Rather than row order, the vector may be column order. The dotproduct is the inner product of the two vectors. In one or moreembodiments, the dot product of each pair of vectors is maintained. Thebending response model may include the pre-computed dot products and/orthe vectors.

In some embodiments, rather than creating dot products, the calibrationdata is stored directly. For example, the bending response model that isused at runtime may include the displacement image and/or normalizeddelta image for each location of the test object. In some embodiments,the bending response model is a single two dimensional matrix. Eachcolumn of the two dimensional matrix may be the flattened imagediscussed above when the test object is at a particular position. Forexample, column 1 of the matrix may correspond to the flattened imagewhen the test object is at position 1, column 2 is the flattened imageis at position 2, etc.

Although the above is discussed with respect to vectors and matrices,virtually any data structure may be used. In particular, one or moreembodiments of the invention are not limited to any particular datastructure.

Using the calibration data, per input object force estimation may beperformed. FIG. 6 shows a flowchart for estimating force during runtimein accordance with one or more embodiments of the invention. In Step601, using sensor electrodes, a raw image of the sensing region isacquired. Acquiring a raw image of the sensing region may be performedusing capacitive sensing, such as using the method discussed above withreference to Step 503.

In Step 603, a delta image is obtained from the raw image in accordancewith one or more embodiments of the invention. In one or moreembodiments, obtaining the delta image may be performed as discussedabove in reference to Step 505. In some embodiments, the delta imageobtained in Step 603 includes a single image that has both force andpositional information. For example, where the same sensor electrodesare arranged to simultaneously detect force and positional information,a single measurement may reflect both a presence of an input object at aparticular position as well as the force applied by the input object. Insome embodiments, the delta image includes at least two separate images,a positional image and a force image. For example, sensor electrodesthat detect positional information may be at least partially differentthan the sensor electrodes that detect force information.

In Step 605, locations of the input objects in the sensing region aredetermined based on the delta image. In other words, the delta image isprocessed to identify the locations. For example, if the delta image isa single image with both force and positional information, the singleimage may be processed to identify portions of the image having peakvalues satisfying a threshold. For example, a determination may be madeas to which portions of the delta image are greater than a threshold. Ifthe delta image is a separate positional image, then the positionalimage is processed to identify the portions of the positional imagesatisfying the threshold. Various processing techniques may be appliedto process the delta image and identify the locations of the inputobject.

In Step 607, a force image is obtained from the delta image inaccordance with one or more embodiments of the invention. If the deltaimage has a separate force image than positional image, then obtainingthe force image is to identify the force image. If the delta imageincludes a single image that has both information, then processing isperformed on the single image to remove the effects of the presence ofthe input object. For example, the processing may be to apply asmoothing method, such as described below with reference to FIG. 7. Byway of another example, the processing may be to apply a least squaresfit and remove outliers which correspond to the input objects as part ofperforming Step 611 discussed below.

In Step 609, the displacement image is determined from the force imagein accordance with one or more embodiments of the invention. Determiningthe displacement image from the force image may be performed asdiscussed above with reference to Step 507 of FIG. 5. Further, asdiscussed above, in some embodiments, the conversion is not performed.

In Step 611, a force estimate is determined for each input object fromthe displacement image, the bending response model, and the locations ofthe input object in accordance with one or more embodiments of theinvention. In general, the force estimate is determined by using thelocations of the input objects to identify the calibration informationin the bending response model. A dot product is performed on the runtimeimage (e.g., force image) with the calibration data and a linear solveis performed using the dot product to obtain an estimation of force foreach separate input object. The performing the linear solve may be alinear least squares fit of the flattened model force images for eachinput object to the current flattened displacement image. One or moreembodiments, therefore, attribute certain portions of the force toparticular input objects such that each input object has a separateestimate of force. In other words, the separate estimate may bedifferent for each input object. Below are more particular methods fordetermining the force estimate.

One technique is to use the locations of the input objects to identifythe corresponding model force images that are obtained when an inputobject is at the respective locations. If a model force image for aparticular location does not exist, an approximation may be performedusing existing model force images to estimate a model force image forthe location touched. Further, a dot product of the model force imagesis performed, if such a precomputed dot product does not exist. A linearsolve is performed to determine the force. In the example technique, thefollowing matrix equation (Eq. 1) may be used.

$\begin{matrix}{{\begin{bmatrix}\left( {{\overset{\rightarrow}{a}}_{1} \cdot {\overset{\rightarrow}{a}}_{1}} \right) & \ldots & \left( {{\overset{\rightarrow}{a}}_{1} \cdot {\overset{\rightarrow}{a}}_{m}} \right) \\\vdots & \ddots & \vdots \\\left( {{\overset{\rightarrow}{a}}_{1} \cdot {\overset{\rightarrow}{a}}_{m}} \right) & \ldots & \left( {{\overset{\rightarrow}{a}}_{m} \cdot {\overset{\rightarrow}{a}}_{m}} \right)\end{bmatrix}\begin{bmatrix}x_{1} \\\vdots \\x_{m}\end{bmatrix}} = \begin{bmatrix}{{\overset{\rightarrow}{a}}_{1} \cdot \overset{\rightarrow}{b}} \\\vdots \\{{\overset{\rightarrow}{a}}_{m} \cdot \overset{\rightarrow}{b}}\end{bmatrix}} & \left( {{Eq}.\mspace{14mu} 1} \right)\end{matrix}$In Eq. 1, {right arrow over (a)}_(i) is a flattened model force imagefor the ith input object, whereby the flattened model force imagematches the position of the ith input object at position i. Thus, {rightarrow over (a)}₁ is the flattened model force image for the first inputobject. x_(i) is the estimate of force for the ith test input object.{right arrow over (b)} is the runtime force image determined in Step 609or 607, depending on whether the displacement image is used.

Another technique uses the cell size location information. In such ascenario, a matrix W may be created that is the combination of modelforce images. For example, each column of W may be a flattened modelforce image for an input object at particular position. In the example,the ith column of W is the flattened model force image obtained for whenthe input object is at position i. The location of the input objects maybe specified in a sparse matrix P, whereby P is an m,n matrix having m*nentries. In matrix P, if the input object is at the location representedby a particular entry, then the particular entry is marked with a 1,otherwise, the entry is marked with a 0. Thus, if the input object spansmultiple consecutive entries, then each of the consecutive entries maybe marked with a 1. Multiplying W*P yields a matrix having only thecalibrated force information for only the positions in which the inputobjects are located. The following Eq. 2 is an example equation forestimating force using matrices W and P.(P ^(T) W ^(T) WP){right arrow over (x)}=P ^(T) W ^(T) {right arrow over(b)}  (Eq. 2)In Eq. 2, P^(T) is the transpose of matrix P and W^(T) is the transposeof matrix W. {right arrow over (x)} is a force vector that includes anestimation of force for each input object position, and {right arrowover (b)} is the measured force image that is obtained in Step 609 or607. For example, the Jacobi method may be used to obtain {right arrowover (x)}. Other techniques and optimizations may be performed todetermine {right arrow over (x)} during runtime. Such techniques may bebased, for example, on P being a sparse matrix. In this secondtechnique, conceptually Eq. 1 may be used with the following change.Instead of reading each flattened model force image {right arrow over(a)}_(i) from memory based on the position of each input object, a morecustomized flattened model force image {right arrow over (a_(i))} isdynamically generated for each input object by combining the flattenedmodel force images obtained using the procedure described with referenceto FIG. 4.1. For example, {right arrow over (a)}_(i)=W{right arrow over(p)}_(i) may be computed, where W is the matrix described above, and{right arrow over (p)}_(i) is the ith column of the matrix P describedabove. The matrix-vector product W{right arrow over (p)}_(i) is equal toa linear combination of the columns of matrix W. The linear combinationis an approximation of the flattened force image corresponding to anobject which covers the grid cells corresponding to the 1s in {rightarrow over (p)}_(i). Then, Eq. 1 may be solved as usual to obtain forceestimates.

In other words, for the second technique described above, for each inputobject on the sensing surface, the sum over each pixel under the inputobject is performed, and the corresponding bending responses arecombined to create a predicted shape of the displacement caused by theinput object. Then, the predicted shapes are linearly combined to fitthe measured displacement, and the coefficients from this linearcombination are the estimated forces for each input object.

As discussed above, when the force image is combined with the positionalimage, the processing may be to apply a least squares fit and removeoutliers as part of performing Step 611. In particular, a linear systemof Eq. 1 is equivalent to a linear least squares fit. If A is the matrixwith columns {right arrow over (a_(l))}, then Eq. 1 is equivalent to thefollowing Equation 3.(A ^(T) A){right arrow over (x)}=A ^(T) {right arrow over (b)}  (Eq. 3)To apply a least squares fit and remove outliers, a weighted leastsquares fit may be performed by solving the following Equation 4.(A ^(T) QA){right arrow over (x)}=A ^(T) Q{right arrow over (b)}  (Eq.4)In Eq. 4, Q has diagonal entries

${q_{ii} = \frac{1}{\left( {b_{i} - \left( {A\;\overset{\rightarrow}{x}} \right)_{i}} \right)^{2}}},$where b_(i) is the ith element of vector {right arrow over (b)}, and(A{right arrow over (x)})_(i) is the ith element of the vector formed bythe product of the matrix A and the force vector {right arrow over (x)}calculated during the previous frame.

In Step 613, an action is performed based on the force estimate inaccordance with one or more embodiments of the invention. For example,the action may be to send a report to the host device of the force oneach input object. In some embodiments, the action is a GUI action, suchas to display data or perform another action. In some embodiments, theaction is to determine to ignore a first input object that is estimatedas having less than a threshold amount of force when a second inputobject has more than a threshold amount of force, where the thresholdsmay be the same or different. Ignoring may be to drop or disregardpositional and/or force information for the ignored input object. Otheractions may be performed without departing from the scope of embodimentsdescribed herein.

Turning to FIG. 7, FIG. 7 shows a flowchart for obtaining a force imagefrom a single image that has both positional information and forceinformation. In Step 701, locations of the input objects are determined.Determining the locations of the input objects may be performed asdiscussed above with reference to Step 605 of FIG. 6.

In Step 703, the curvature of the image at the locations is determinedin accordance with one or more embodiments of the invention. In one ormore embodiments, the curvature is obtained by obtaining the twodimensional second derivative, or the Laplacian, of the image. Thesecond derivative is negative at the location of the input objects.Notably, the locations of the input objects may be determined as part ofdetermining Step 703 based on the negative aspect of the secondderivative.

In Step 705, the curvature is smoothed at the locations a defined numberof times to obtain the force image. For example, Euler's method may beapplied to simulate anisotropic diffusion in order to selectively smoothaway the peaks caused by input objects. The pixels underneath the inputobjects are forced to have a curvature that is around the respectiveinput objects, without having the curvature of the input objects. Thus,the force effects reflected in the image may be separated from the touchportion of the effects in the image without having the touch signalpollute the force signal.

FIGS. 8 and 9 show examples in accordance with one or more embodimentsof the invention. The following example is for explanatory purposes onlyand not intended to limit the scope of the invention.

FIG. 8 shows an example for smoothing the curvature of the input object.In particular, graph A (803), graph B (805), and graph C (807) are topperspective views of the graph of the image at time t1, t2, and t3,respectively. Graph D (813), graph E (815), and graph F (817) are sideviews of the graph of the image at time t1, t2, and t3, respectively. Asshown in graph A (803) and graph D (813) of FIG. 8, at time t1, thecurvature of the central input object is large. Smoothing is performedon the middle input object of the graph to create graph B (805) andgraph E (815) at time t2. Thus, the curvature of the middle input objectposition remains in time t2, but the middle input object is not aspronounced as at time t1. Smoothing is further performed on the middleinput object of the graph to create graph C (807) and graph F (817) attime t3. Thus, the curvature of the middle input object position is suchthat the middle input object disappears and only the effects of forceremain. Accordingly, the force image may be processed to determine theamount of force for each location of an input object.

FIG. 9 shows an example diagram (900) in accordance with one or moreembodiments of the invention. As shown in FIG. 9, in the graph (902) ofthe image of touch data, two input objects are located at position X(904) and Y (906) on the sensing region. Based on the position of theinput objects, model force images (e.g., calibration data) a₁ (908) anda₂ (910) are obtained. In particular, a₁ (908) is the model force imagefor an input object located at position X (904) and a₂ (910) is themodel force image for an input object located at position Y (906).Continuing with FIG. 9, the model force images are multiplied by theruntime force image (916) to obtain raw force 1 (912) and raw force 2(914). Raw force 1 (912) is the force of the input object at position X(904) and raw force 2 (914) is the force of the input object at positionY (906). Algebraically, determining the raw force may be performed bysolving the following equation Eq. 5.

$\begin{matrix}{{\begin{bmatrix}\left( {{\overset{\rightarrow}{a}}_{1} \cdot {\overset{\rightarrow}{a}}_{1}} \right) & \left( {{\overset{\rightarrow}{a}}_{1} \cdot {\overset{\rightarrow}{a}}_{2}} \right) \\\left( {{\overset{\rightarrow}{a}}_{1} \cdot {\overset{\rightarrow}{a}}_{2}} \right) & \left( {{\overset{\rightarrow}{a}}_{2} \cdot {\overset{\rightarrow}{a}}_{2}} \right)\end{bmatrix}\begin{bmatrix}{\overset{\rightarrow}{x}}_{1} \\{\overset{\rightarrow}{x}}_{2}\end{bmatrix}} = \begin{bmatrix}{{\overset{\rightarrow}{a}}_{1} \cdot \overset{\rightarrow}{b}} \\{{\overset{\rightarrow}{a}}_{2} \cdot \overset{\rightarrow}{b}}\end{bmatrix}} & \left( {{Eq}.\mspace{14mu} 5} \right)\end{matrix}$

Although FIG. 9 shows only two input objects, one or more embodimentsmay be used to obtain the force for any number of input objects. Forexample, the per input object force estimation may be obtained for teninput objects using the techniques described herein.

Thus, the embodiments and examples set forth herein were presented inorder to best explain the present invention and its particularapplication and to thereby enable those skilled in the art to make anduse the invention. However, those skilled in the art will recognize thatthe foregoing description and examples have been presented for thepurposes of illustration and example only. The description as set forthis not intended to be exhaustive or to limit the invention to theprecise form disclosed.

What is claimed is:
 1. A processing system for multiple touch inputobject force estimation, comprising: sensor circuitry configured toacquire a plurality of touch force measurements of a sensing region on asurface using a plurality of sensor electrodes, wherein the surface ischaracterized by a bending response model representative of adistribution of non-uniform bending coefficients; processing circuitryconnected to the sensor circuitry and configured to: obtain a deltaimage of the sensing region using the plurality of touch forcemeasurements; identify a plurality of touch locations of a plurality oftouch input objects in the sensing region using the delta image;identify a plurality of flattened model force images using the pluralityof touch locations of the plurality of touch input objects, wherein eachflattened model force image of the plurality of flattened model forceimages is a one-dimensional vector corresponding to a respectivetwo-dimensional calibration information for a respective input object,and the two-dimensional calibration information comprises calibrationdata for a respective individual location on the surface according tothe bending response model; determine a location-based force estimatefor each input object of the plurality of input objects by performing alinear solve using a one-dimensional vector obtained from the deltaimage and the plurality of flattened model force images corresponding tothe plurality of touch input objects; and perform an action based on theforce estimate of each input object of the plurality of input objects.2. The processing system of claim 1, wherein each flattened model forceimage of the plurality of flattened model force images corresponds to aunique model force image for each cell of the sensing region.
 3. Theprocessing system of claim 2, wherein the unique model force image isgenerated by applying a model input object to a cell on the sensingregion with a defined force to obtain a force value for each cell andnormalizing the force value based on the defined force.
 4. Theprocessing system of claim 1, wherein the delta image comprises a forceimage and a positional image.
 5. The processing system of claim 1,wherein performing the linear solve comprises using the plurality offlattened model force images with a raw force image obtained from thedelta image.
 6. The processing system of claim 1, wherein the deltaimage comprises a force image and a positional image, the positionalimage being separate in the delta image from the force image, whereinidentifying the plurality of locations is from the positional image. 7.The processing system of claim 1, wherein the processing circuitry isfurther configured to: determine a curvature of the delta image at theplurality of locations in the delta image; and smooth the curvature atthe plurality of locations a defined number of times to obtain a forceimage.
 8. A method for multiple touch input object force estimation,comprising: obtaining a delta image of a sensing region on a surfaceusing a plurality of sensor electrodes, wherein the surface ischaracterized by a bending response model representative of adistribution of non-uniform bending coefficients; identifying aplurality of touch locations of a plurality of touch input objects inthe sensing region using the delta image; identifying a plurality offlattened model force images using the plurality of touch locations ofthe plurality of touch input objects, wherein each flattened model forceimage of the plurality of flattened model force images is aone-dimensional vector corresponding to a respective two-dimensionalcalibration information for a respective input object, and thetwo-dimensional calibration information comprises calibration data for arespective individual location on the surface according to the bendingresponse model; determining a location-based force estimate for eachinput object of the plurality of input objects by performing a linearsolve using a one-dimensional vector obtained from the delta image andthe plurality of flattened model force images corresponding to theplurality of touch input objects; and performing an action based on theforce estimate of each input object of the plurality of input objects.9. The method of claim 8, wherein each flattened model force image ofthe plurality of flattened model force images corresponds to a uniquemodel force image for each cell of the sensing region.
 10. The method ofclaim 9, wherein the unique model force image is generated by applying amodel input object to a cell on the sensing region with a defined forceto obtain a force value for each cell, and normalizing the force valuebased on the defined force.
 11. The method of claim 8, wherein the deltaimage comprises a force image and a positional image.
 12. The method ofclaim 8, wherein performing the linear solve comprises using theplurality of flattened model force images with a raw force imageobtained from the delta image.
 13. The method of claim 8, wherein thedelta image comprises a force image and a positional image, thepositional image being separate in the delta image from the force image,wherein identifying the plurality of locations is from the positionalimage.
 14. The method of claim 8, further comprising: determining acurvature of the delta image at the plurality of locations in the deltaimage; and smoothing the curvature at the plurality of locations adefined number of times to obtain a force image.
 15. An input device formultiple touch input object force estimation, comprising: sensorcircuitry configured acquire a plurality of touch force measurements ofa sensing region on a surface using a plurality of sensor electrodes,wherein the surface is characterized by a bending response modelrepresentative of a distribution of non-uniform bending coefficients;processing circuitry connected to the sensor circuitry and configuredto: obtain a delta image of the sensing region using the plurality oftouch force measurements; identify a plurality of touch locations of aplurality of touch input objects in the sensing region using the deltaimage; identify a plurality of flattened model force images using theplurality of touch locations of the plurality of touch input objects,wherein each flattened model force image of the plurality of flattenedmodel force images is a one-dimensional vector corresponding to arespective two-dimensional calibration information for a respectiveinput object, and the two-dimensional calibration information comprisescalibration data for a respective individual location on the surfaceaccording to the bending response model; determine a location-basedforce estimate for each input object of the plurality of input objectsby performing a linear solve using a one-dimensional vector obtainedfrom the delta image and the plurality of flattened model force imagescorresponding to the plurality of touch input objects; and perform anaction based on the force estimate of each input object of the pluralityof input objects.
 16. The input device of claim 15, wherein performingthe linear solve comprises using the plurality of flattened model forceimages with a raw force image obtained from the delta image.
 17. Theinput device of claim 15, wherein the processing circuitry is furtherconfigured to: determine a curvature of the delta image at the pluralityof locations in the delta image; and smooth the curvature at theplurality of locations a defined number of times to obtain a forceimage.